Bayesian refinement of association signals for 14 loci in 3 common diseases

Maller, Julian B., McVean, Gilean, Byrnes, Jake, Vukcevic, Damjan, Palin, Kimmo, Su, Zhan, Howson, Joanna M. M., Auton, Adam, Myers, Simon, Morris, Andrew, Pirinen, Matti, Brown, Matthew A., Burton, Paul R., Caulfield, Mark J., Compston, Alastair, Farrall, Martin, Hall, Alistair S., Hattersley, Andrew T., Hill, Adrian V. S., Mathew, Christopher G., Pembrey, Marcus, Satsangi, Jack, Stratton, Michael R., Worthington, Jane, Craddock, Nicholas John ORCID: https://orcid.org/0000-0003-2171-0610, Hurles, Matthew, Ouwehand, Willem, Parkes, Miles, Rahman, Nazneen, Duncanson, Audrey, Todd, John A., Kwiatkowski, Dominic P., Samani, Nilesh J., Gough, Stephen C. L., McCarthy, Mark I., Deloukas, Panagiotis and Donnelly, Peter 2012. Bayesian refinement of association signals for 14 loci in 3 common diseases. Nature Genetics 44 (12) , pp. 1294-1301. 10.1038/ng.2435

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Abstract

To further investigate susceptibility loci identified by genome-wide association studies, we genotyped 5,500 SNPs across 14 associated regions in 8,000 samples from a control group and 3 diseases: type 2 diabetes (T2D), coronary artery disease (CAD) and Graves' disease. We defined, using Bayes theorem, credible sets of SNPs that were 95% likely, based on posterior probability, to contain the causal disease-associated SNPs. In 3 of the 14 regions, TCF7L2 (T2D), CTLA4 (Graves' disease) and CDKN2A-CDKN2B (T2D), much of the posterior probability rested on a single SNP, and, in 4 other regions (CDKN2A-CDKN2B (CAD) and CDKAL1, FTO and HHEX (T2D)), the 95% sets were small, thereby excluding most SNPs as potentially causal. Very few SNPs in our credible sets had annotated functions, illustrating the limitations in understanding the mechanisms underlying susceptibility to common diseases. Our results also show the value of more detailed mapping to target sequences for functional studies.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG) Medicine
Subjects:	Q Science > QH Natural history > QH426 Genetics
Publisher:	Nature Publishing Group
ISSN:	1061-4036
Last Modified:	21 Oct 2022 10:52
URI:	https://orca.cardiff.ac.uk/id/eprint/41570

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